Evgenii Kovrigin (C) 2022

 



  KovriginNMR Workflows: Introduction


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The main goal of KovriginNMR is to you enable automation of complex and flexible NMR workflows. The intended user of KovriginNMR is an NMR spectroscopist with experience of operating Bruker Topspin software. Unlike IconNMR, KovriginNMR does not shield the NMR user from a spectrometer or restricts his/her actions: entire range of capabilities of Topspin software remains accessible. KovriginNMR provides a programming environment on top of Topspin and Spooler capabilities. KovriginNMR functions enable fast development of complex experimental routines involving multiple samples and multiple experiments. You are able to automate as much or as little of your workflow as desired.

Generally, when the workflow involves only a couple of samples and a small number of experiments, most NMR users can choose to utilize the Spooler function of Topspin. However, as soon as the number of sample increases and set of experiments to be performed becomes complex and different for different samples, it becomes more effective to utilize KovriginNMR. The software may be started from user's own account (no need for superuser privileges). The simplest workflows would involve only several lines of Python code.

It will be very helpful for an advanced user of KovriginNMR to have some knowledge of Python programming language. Beginner users of KovriginNMR may only need a general familiarity with Python if their NMR manager prepares basic KovriginNMR scripts for them. KovriginNMR software distribution includes example scripts for different tasks.

Topspin includes helpful manuals on Python in the Help:Manuals (docs): Programming Manuals section. Please, see Python Tutorial for general overview and examples, Python Introduction for more detailed Python version used in Topspin (called Jython), and Python Programming for specific commands to access Topspin functions.

KovriginNMR is free for academic users. Advanced users are allowed to create their own extensions for KovriginNMR, as long as they retain all copyright marks in the original Python code.


 

 

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Evgenii Kovrigin (C) 2022